Skip to content

query search doc #1521

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: major
Choose a base branch
from
Open

query search doc #1521

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
36 changes: 35 additions & 1 deletion docs/user-interface/panes/database-products.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,41 @@ parent: Panes

## Elements
### Quick Search
A search bar at the top of the pane allows you to quickly filter and find specific database products by typing keywords. You can also build complex queries by using an equal sign (`=`) before a Pandas query syntax.
A search bar at the top of the pane allows you to quickly filter and find specific database products by typing keywords.
You can also build complex queries by using an equal sign (`=`) before a Pandas query syntax.

#### Query Search
You can search for exact items by writing queries using the
[pandas query language](https://pandas.pydata.org/docs/dev/reference/api/pandas.DataFrame.query.html).
To do this, you must start your search with `=` and then write the query.
If the query is incorrect, the search bar will turn red and no search is done.

> [!TIP]
> A [pandas query](https://pandas.pydata.org/docs/dev/reference/api/pandas.DataFrame.query.html)
> makes use of logical operations like:
> - `==` equals
> - `!=` does not equal
> - `~` NOT
> - `&` AND
> - `|` OR
> - `(` and `)` to chain logical operations
>
> You can also make use of other pandas operations to check for data like:
> - `column.str` to ensure all content of that column is interpreted as text
> - `column.str.contains()` to search within text (use `.contains("text", False)` for case in-sensitive)
> - `column.isin()` to check if values are in a list of items

Below are some examples of queries, getting progressively more complex:

| Query | Description |
|-----------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|
| `=product=="apple"` | Find all rows where column `product` is (`==`) **Exactly** `apple` |
| `=product!="apple"` | Find all rows where column `product` is (`!=`) **not** `apple` |
| `=product.str.contains("apple")` | Find all rows where column `product` contains `apple` |
| `=~product.str.contains("apple")` | Find all rows where column `product` does not (`~`) contain `apple` |
| `=product.isin(["apple", "pear"])` | Find all rows where column `product` matches **Exactly** an item in `["apple", "pear"]` |
| `=(product.str.contains("apple") \| product.str.contains("pear"))` | Find all rows where column `product` contains `apple` OR (`\|`) `pear` |
| `=(product.str.contains("apple") & ~activity.str.contains("market"))` | Find all rows where column `product` contains `apple` AND (`&`) column `activity` does not contain `market` |

### Products View
The Products view displays a list of all the products in the currently selected database, along with some key attributes like: type, unit, and location. If the database is based on the [Functional SQLite backend](../../advanced-topics/multifunctional-databases), only products are shown, grouped by their processors.
Expand Down
Loading